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研究生:劉政雄
研究生(外文):Liu, Cheng Hsiung
論文名稱:利用攝影機校正、表面反投影以及二維模型比對技巧從單張影像中擷取物體形狀及表面資料作立體物辨認
論文名稱(外文):RECOGNITION OF 3D OBJECTS BY SINGLE CAMERA VIEWS USING CAMERA CALIBRATION, SURFACE BACKPROJECTION, AND 2D MODEL MATCHING TECHNIQUES BASED ON OBJECT SHAPE AND SURFACE PATTERN INFORMATION
指導教授:蔡文祥蔡文祥引用關係
指導教授(外文):Prof. Tsai, Wen Hsiang
學位類別:博士
校院名稱:國立交通大學
系所名稱:資訊工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:1993
畢業學年度:81
語文別:英文
論文頁數:128
中文關鍵詞:攝影機校正表面反投影二維模型比對距離加權相關度
外文關鍵詞:camera calibrationsurface backprojection2D model matching
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本論文提出結合攝影機校正、表面反投影以及二維模型比對技巧從單張影
像中辨認三種不同立體物之新方法。三種不同之立體物包括在商品以及工
業元件中常見之長方體、圓柱體以及正角柱體。本論文不只利用物體之形
狀資料並利用了物體之表面資料來辨認物體。對每類物體,不同大小尺寸
或者不同表面資料之物體皆可加以辨認。要辨識待辨認物體,首先利用待
辨認物體之單張影像資料求出攝影機參數以及物體大小之公式解。此公式
解能比其他方法更快速求出攝影機參數。此攝影機校正技巧,基本上是利
用物體表面之直線或是曲線資料求得。而後利用表面反投影技巧將物體之
表面重建;此技巧將三度空間之表面資料轉換成一些二度空間之平面資料
,如此使得接下去之模型比對得以在二度空間進行。最後,在模型比對步
驟中每一平面資料根據(DWC)從資料庫中找出最適當之模型,將此待
辨認之物體認定為此模型。實驗數據顯示此方法確實可行。
A new approach to recognition of three different classes of 3D
objects by single camera views using a combination of camera
calibration, surface backprojection, and 2D model matching
techniques are proposed. The three classes of 3D objects are
cuboids, cylinders, and regular prisms, which are commonly seen
in commercial products and industrial parts. Not only the
silhouette shape but also the surface pattern of the object are
utilized in the recognition scheme. For each class, objects of
both different sizes and different surface patterns can be
recognized. To recognize an input object of each class, a new
camera calibration technique is first employed to compute the
camera parameters as well as the object dimension parameters
analytically using a single camera view of the object. The
availability of the analytical solutions of the camera
parameters makes the proposed technique faster in parameter
computation than other camera calibration approaches requiring
iterative parameter computation processes. The calibration
technique is based on the use of the information of the lines
or curves formed by the intersections of the object surfaces. A
surface backprojection technique is then adopted to reconstruct
the pattern on each surface patch of the input object. This
technique transforms the 3D surface data into a set of 2D
surface patch patterns, which make the subsequent model
matching process becomes 2D in nature. Finally, in the model
matching process, each surface patch pattern is matched with
those of each object model using the distance weighted
correlation measure. Experimental results show the feasibility
of the proposed approach.
ABSTRACT IN CHINESE
ABSTRACT IN ENGLISH
ACKNOWLEDGMENTS
TABLE OF CONTENTS
LIST OF FIGURES
LIST OF TABLES
CHAPTER 1 INTRODUCTION
1.1 Motivation
1.2 Survey of Related Research
1.3 Overview of Proposed Apporaches
1.4 Dissertation Organization
CHAPTER 2 MATHEMATICAL MODELS FOR COORDINATE TRANSFORMATION AND SURFACE BACKPROJECTION
2.1 Coordinate Systems and Transformations
2.2 Surface Backprojection
CHAPTER 3 RECOGNITION OF CUBOIDAL OBJECTS
3.1 Overview of Proposed Approach
3.2 Proposed Camera Calibration Technique
3.3 Method for Reconstruct Surface Patch Patterns Using Surface Backprojection Technique
3.4 Learning and Recognition Phases
3.5 Experimental Results
3.6 Summary
CHAPTER 4 RECOGNITION OF CYLINDRICAL OBJECTS
4.1 Overview of Proposed Approach
4.2 Proposed Camera Calibration Technique
4.3 Method For Reconstructing Surface patch Patterns Using Backprojection Techniques
4.4 Learning and Recognition Phases
4.5 Experimental Results
4.6 summary
CHAPTER 5 RECOGNITION OF REGULAR-SHAPED OBJECTS
5.1 Overview of Proposed approach
5.2 Proposed Camera Calibration Technique
5.3 Method for Reconstructing Surface Patch Patterns Using Backprojection Technique
5.4 Learning and Recognition Phases
5.5 Experimental Results
5.6 Summary
CHAPTER 6 CONCLUSIONS, DISCUSSIONS, AND SUGGESTIONS FOR FUTURE RESEARCH
6.1 Conclusions
6.2 Discussions
6.3 Suggestions for Future Research
REFERENCES
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